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Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study

Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study
Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study
Background
Breathing pattern disorders are frequently reported in uncontrolled asthma. At present, this is primarily assessed by questionnaires, which are subjective. Objective measures of breathing pattern components may provide additional useful information about asthma control. This study examined whether respiratory timing parameters and thoracoabdominal (TA) motion measures could predict and classify levels of asthma control.
Methods
One hundred twenty-two asthma patients at STEP 2- STEP 5 GINA asthma medication were enrolled. Asthma control was determined by the Asthma Control Questionnaire (ACQ7-item) and patients divided into ‘well controlled’ or ‘uncontrolled’ groups. Breathing pattern components (respiratory rate (RR), ratio of inspiration duration to expiration duration (Ti/Te), ratio of ribcage amplitude over abdominal amplitude during expiration phase (RCampe/ABampe), were measured using Structured Light Plethysmography (SLP) in a sitting position for 5-min. Breath-by-breath analysis was performed to extract mean values and within-subject variability (measured by the Coefficient of Variance (CoV%). Binary multiple logistic regression was used to test whether breathing pattern components are predictive of asthma control. A post-hoc analysis determined the discriminant accuracy of any statistically significant predictive model.
Results
Fifty-nine out of 122 asthma patients had an ACQ7-item < 0.75 (well-controlled asthma) with the rest being uncontrolled (n = 63). The absolute mean values of breathing pattern components did not predict asthma control (R2 = 0.09) with only mean RR being a significant predictor (p < 0.01). The CoV% of the examined breathing components did predict asthma control (R2 = 0.45) with all predictors having significant odds ratios (p < 0.01). The ROC curve showed that cut-off points > 7.40% for the COV% of the RR, > 21.66% for the CoV% of Ti/Te and > 18.78% for the CoV% of RCampe/ABampe indicated uncontrolled asthma.
Conclusion
The within-subject variability of timing parameters and TA motion can be used to predict asthma control. Higher breathing pattern variability was associated with uncontrolled asthma suggesting that irregular resting breathing can be an indicator of poor asthma control.
2054-7064
Barney, Anna
bc0ee7f7-517a-4154-ab7d-57270de3e815
Sakkatos, Panagiotis
593565b6-d4df-46a7-802c-76ae57223f93
Bruton, Anne
9f8b6076-6558-4d99-b7c8-72b03796ed95
Barney, Anna
bc0ee7f7-517a-4154-ab7d-57270de3e815
Sakkatos, Panagiotis
593565b6-d4df-46a7-802c-76ae57223f93
Bruton, Anne
9f8b6076-6558-4d99-b7c8-72b03796ed95

Barney, Anna, Sakkatos, Panagiotis and Bruton, Anne (2021) Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study. Asthma Research and Practice, 7 (5).

Record type: Article

Abstract

Background
Breathing pattern disorders are frequently reported in uncontrolled asthma. At present, this is primarily assessed by questionnaires, which are subjective. Objective measures of breathing pattern components may provide additional useful information about asthma control. This study examined whether respiratory timing parameters and thoracoabdominal (TA) motion measures could predict and classify levels of asthma control.
Methods
One hundred twenty-two asthma patients at STEP 2- STEP 5 GINA asthma medication were enrolled. Asthma control was determined by the Asthma Control Questionnaire (ACQ7-item) and patients divided into ‘well controlled’ or ‘uncontrolled’ groups. Breathing pattern components (respiratory rate (RR), ratio of inspiration duration to expiration duration (Ti/Te), ratio of ribcage amplitude over abdominal amplitude during expiration phase (RCampe/ABampe), were measured using Structured Light Plethysmography (SLP) in a sitting position for 5-min. Breath-by-breath analysis was performed to extract mean values and within-subject variability (measured by the Coefficient of Variance (CoV%). Binary multiple logistic regression was used to test whether breathing pattern components are predictive of asthma control. A post-hoc analysis determined the discriminant accuracy of any statistically significant predictive model.
Results
Fifty-nine out of 122 asthma patients had an ACQ7-item < 0.75 (well-controlled asthma) with the rest being uncontrolled (n = 63). The absolute mean values of breathing pattern components did not predict asthma control (R2 = 0.09) with only mean RR being a significant predictor (p < 0.01). The CoV% of the examined breathing components did predict asthma control (R2 = 0.45) with all predictors having significant odds ratios (p < 0.01). The ROC curve showed that cut-off points > 7.40% for the COV% of the RR, > 21.66% for the CoV% of Ti/Te and > 18.78% for the CoV% of RCampe/ABampe indicated uncontrolled asthma.
Conclusion
The within-subject variability of timing parameters and TA motion can be used to predict asthma control. Higher breathing pattern variability was associated with uncontrolled asthma suggesting that irregular resting breathing can be an indicator of poor asthma control.

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Published date: 6 April 2021

Identifiers

Local EPrints ID: 509761
URI: http://eprints.soton.ac.uk/id/eprint/509761
ISSN: 2054-7064
PURE UUID: 60324603-418f-457b-85af-d8ebefabcd44
ORCID for Anna Barney: ORCID iD orcid.org/0000-0002-6034-1478
ORCID for Anne Bruton: ORCID iD orcid.org/0000-0002-4550-2536

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Date deposited: 04 Mar 2026 17:47
Last modified: 05 Mar 2026 02:35

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Contributors

Author: Anna Barney ORCID iD
Author: Panagiotis Sakkatos
Author: Anne Bruton ORCID iD

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